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ISPRS Int. J. Geo-Inf. 2017, 6(9), 287; doi:10.3390/ijgi6090287

Topographic Correction to Landsat Imagery through Slope Classification by Applying the SCS + C Method in Mountainous Forest Areas

1
Cuerpo Académico UAGro CA-93 Riesgos Naturales y Geotecnología, Universidad Autónoma de Guerrero, Av/Lázaro Cárdenas s/n, CU, Chilpancingo 39070, Guerrero, Mexico
2
Departamento de Tecnología Química y Energética, Tecnología Química y Ambiental y Tecnología Mecánica, Universidad Rey Juan Carlos, C/Tulipán s/n, Móstoles 28933, Madrid, Spain
3
Geography Group, Departamento de Ciencias de la Educación, Lenguaje, Cultura y Artes, Ciencias Histórica-Jurídicas y Humanísticas y Lenguas Modernas, Facultad de Ciencias Jurídicas y Sociales, Universidad Rey Juan Carlos, Paseo de los Artilleros s/n, Vicálvaro 28032, Madrid, Spain
*
Author to whom correspondence should be addressed.
Received: 5 June 2017 / Revised: 11 August 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
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Abstract

The aim of the topographic normalization of remotely sensed imagery is to reduce reflectance variability caused by steep terrain and thus improve further processing of images. A process of topographic correction was applied to Landsat imagery in a mountainous forest area in the south of Mexico. The method used was the Sun Canopy Sensor + C correction (SCS + C) where the C parameter was differently determined according to a classification of the topographic slopes of the studied area in nine classes for each band, instead of using a single C parameter for each band. A comparative, visual, and numerical analysis of the normalized reflectance was performed based on the corrected images. The results showed that the correction by slope classification improves the elimination of the effect of shadows and relief, especially in steep slope areas, modifying the normalized reflectance values according to the combination of slope, aspect, and solar geometry, obtaining reflectance values more suitable than the correction by non-slope classification. The application of the proposed method can be generalized, improving its performance in forest mountainous areas. View Full-Text
Keywords: Landsat; topographic correction; SCS + C (sun canopy sensor + correction); slope classification; mountainous areas Landsat; topographic correction; SCS + C (sun canopy sensor + correction); slope classification; mountainous areas
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MDPI and ACS Style

Vázquez-Jiménez, R.; Romero-Calcerrada, R.; Ramos-Bernal, R.N.; Arrogante-Funes, P.; Novillo, C.J. Topographic Correction to Landsat Imagery through Slope Classification by Applying the SCS + C Method in Mountainous Forest Areas. ISPRS Int. J. Geo-Inf. 2017, 6, 287.

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